🎬 Movie Recommender System

A content-based movie recommendation system using machine learning to suggest similar movies based on genres, keywords, cast, and crew.

🚀 Live Demo

Try it here: https://willowscosmic-movie-recommender-model-app-fphnyg.streamlit.app/

✨ Features

• 🎬 4,806 movies from TMDB 5000 dataset
• 🤖 Content-based filtering using TF-IDF and Cosine Similarity
• 🖼️ Real-time movie poster fetching via TMDb API
• ⚡ Fast recommendations with Streamlit caching
• 📱 Responsive design

🛠️ Tech Stack

• Python - Core programming language
• Scikit-learn - TF-IDF vectorization and similarity calculation
• Streamlit - Web framework
• Pandas - Data processing
• TMDb API - Movie posters and metadata
• Google Drive - Model storage
• Streamlit Cloud - Deployment

📊 How It Works

1. Combines movie features (genres, keywords, cast, crew, overview)
2. Vectorizes text data using TF-IDF
3. Calculates cosine similarity between movies
4. Returns top 5 most similar movies
5. Fetches posters from TMDb API